title: Identifying radiation exposure biomarkers from mouse blood transcriptome.
abstract: Ionising radiation is a pleiotropic stress agent that may induce a variety of adverse effects. Molecular biomarker approaches possess promise to assess radiation exposure, however, the pleiotropic nature of ionising radiation induced transcriptional responses and the historically poor inter-laboratory performance of omics-derived biomarkers serve as barriers to identification of unequivocal biomarker sets. Here, we present a whole-genome survey of the murine transcriptomic response to physiologically relevant radiation doses, 2 Gy and 8 Gy. We used this dataset with the Random Forest algorithm to correctly classify independently generated data and to identify putative metabolite biomarkers for radiation exposure.
authors.affiliation: Department of Biochemistry and Molecular and Cellular Biology, and Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC 20057, USA. hyduke@ucsd.edu
authors.forename: Daniel R
authors.initials: DR
authors.lastname: Hyduke
authors.forename: Evagelia C
authors.initials: EC
authors.lastname: Laiakis
authors.forename: Heng-Hong
authors.initials: HH
authors.lastname: Li
authors.forename: Albert J
authors.initials: AJ
authors.lastname: Fornace
mesh_terms: D000818:Animals; D015415:Biomarkers / Q000097:blood*; D004307:Dose-Response Relationship, Radiation; D005720:Gamma Rays; D016678:Genome; D051379:Mice; D011829:Radiation Dosage; D011839:Radiation, Ionizing; D059467:Transcriptome / Q000528:radiation effects*
chemical_list: D015415:Biomarkers